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Abstract Background Cancer-associated fibroblasts (CAFs) are essential stromal components in the tumor microenvironment of hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) infection induces pathological changes such as liver fibrosis/cirrhosis and HCC. The aim of this research was to explore the novel mediators of CAFs to modulate HBV cirrhosis-HCC progression. Methods The single-cell transcriptome data of HCC were divided into subsets, and the significant subset related to fibrotic cells, along with biological function, and clinical information of HCC was revealed by integrated data analyses. The cell communication, cells communicated weight analysis of signaling pathways, and key genes in signaling pathways analysis of significant CAFs subclasses were conducted to discover the novel gene of CAFs. Bioinformatics, vitro and HBV transfection assays were used to verify the novel gene is an important target for promoting the progression HBV cirrhosis-HCC progression. Results Fibroblasts derived from HCC single-cell data could be separated into three cell subclasses (CAF0-2), of which CAF2 was associated with the HCC clinical information. Fibroblasts have opposite developmental trajectories to immune B cells and CD8 + T cells. CAF0-2 had strong interaction with B cells and CD8 + T cells, especially CAF2 had the highest interaction frequency and weight with B cells and CD8 + T cells. Moreover, PTN participated in CAF2-related pathways involved in the regulation of cell communication, and the interactions among CAF2 and PTN contributed the most to B cells and CD8 + T cells. Furthermore, the genes of PTN, SDC1, and NCL from PTN signaling were highest expression in CAF2, B cells, and CD8 + T cells, respectively, and the interaction of PTN- SDC1 and PTN- NCL contributed most to the interaction of CAF2- B cells and CAF2-CD8 + T cells. Bioinformatics and vitro experiments confirm PTN was upregulated in HCC and promoted the proliferation of tumor cells, and HBV infection could initiate PTN to perform cirrhosis-HCC progression. Conclusion Our findings revealed CAF was associated with hepatocarcinogenesis, and the functional importance of B cells and CD8 + T cells in modulating CAF in HCC. Importantly, PTN maybe a novel mediator of CAF to mediate HBV cirrhosis-HCC progression.

Abstract Breast cancer (BRCA) is the primary cause of mortality among females globally. The combination of advanced genomic analysis with proteomics characterization to construct a protein prognostic model will help to screen effective biomarkers and find new therapeutic directions. This study obtained proteomics data from The Cancer Proteome Atlas (TCPA) dataset and clinical data from The Cancer Genome Atlas (TCGA) dataset. Kaplan–Meier and Cox regression analyses were used to construct a prognostic risk model, which was consisted of 6 proteins (CASPASE7CLEAVEDD198, NFKBP65-pS536, PCADHERIN, P27, X4EBP1-pT70, and EIF4G). Based on risk curves, survival curves, receiver operating characteristic curves, and independent prognostic analysis, the protein prognostic model could be viewed as an independent factor to accurately predict the survival time of BRCA patients. We further validated that this prognostic model had good predictive performance in the GSE88770 dataset. The expression of 6 proteins was significantly associated with the overall survival of BRCA patients. The 6 proteins and encoding genes were differentially expressed in normal and primary tumor tissues and in different BRCA stages. In addition, we verified the expression of 3 differential proteins by immunohistochemistry and found that CDH3 and EIF4G1 were significantly higher in breast cancer tissues. Functional enrichment analysis indicated that the 6 genes were mainly related to the HIF-1 signaling pathway and the PI3K-AKT signaling pathway. This study suggested that the prognosis-related proteins might serve as new biomarkers for BRCA diagnosis, and that the risk model could be used to predict the prognosis of BRCA patients.

Abstract Background There are multiple promising treatment strategies for central nervous system trauma and disease. However, to develop clinically potent and safe treatments, models of human-specific conditions are needed to complement in vitro and in vivo animal model-based studies. Methods We established human brain stem and spinal cord (cross- and longitudinal sections) organotypic cultures (hOCs) from first trimester tissues after informed consent by donor and ethical approval by the Regional Human Ethics Committee, Stockholm (lately referred to as Swedish Ethical Review Authority), and The National Board of Health and Welfare, Sweden. We evaluated the stability of hOCs with a semi-quantitative hOC score, immunohistochemistry, flow cytometry, Ca2+ signaling, and electrophysiological analysis. We also applied experimental allogeneic human neural cell therapy after injury in the ex vivo spinal cord slices. Results The spinal cord hOCs presented relatively stable features during 7–21 days in vitro (DIV) (except a slightly increased cell proliferation and activated glial response). After contusion injury performed at 7 DIV, a significant reduction of the hOC score, increase of the activated caspase-3+ cell population, and activated microglial populations at 14 days postinjury compared to sham controls were observed. Such elevation in the activated caspase-3+ population and activated microglial population was not observed after allogeneic human neural cell therapy. Conclusions We conclude that human spinal cord slice cultures have potential for future structural and functional studies of human spinal cord development, injury, and treatment strategies.

Abstract Background Renal cell carcinoma (RCC) is the most common kidney cancer and includes several molecular and histological subtypes with different clinical characteristics. The combination of DNA methylation and gene expression data can improve the classification of tumor heterogeneity, by incorporating differences at the epigenetic level and clinical features. Methods In this study, we identified the prognostic methylation and constructed specific prognosis-subgroups based on the DNA methylation spectrum of RCC from the TCGA database. Results Significant differences in DNA methylation profiles among the seven subgroups were revealed by consistent clustering using 3389 CpGs that indicated that were significant differences in prognosis. The specific DNA methylation patterns reflected differentially in the clinical index, including TNM classification, pathological grade, clinical stage, and age. In addition, 437 CpGs corresponding to 477 genes of 151 samples were identified as specific hyper/hypomethylation sites for each specific subgroup. A total of 277 and 212 genes corresponding to DNA methylation at promoter sites were enriched in transcription factor of GKLF and RREB-1, respectively. Finally, Bayesian network classifier with specific methylation sites was constructed and was used to verify the test set of prognoses into DNA methylation subgroups, which was found to be consistent with the classification results of the train set. DNA methylation-based classification can be used to identify the distinct subtypes of renal cell carcinoma. Conclusions This study shows that DNA methylation-based classification is highly relevant for future diagnosis and treatment of renal cell carcinoma as it identifies the prognostic value of each epigenetic subtype.

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